Resting state brain function analysis using concurrent BOLD in ASL perfusion fMRI

Abstract

The past decade has seen astounding discoveries about resting-state brain activity patterns in normal brain as well as their alterations in brain diseases. While the vast majority of resting-state studies are based on the blood-oxygen-level-dependent (BOLD) functional MRI (fMRI), arterial spin labeling (ASL) perfusion fMRI can simultaneously capture BOLD and cerebral blood flow (CBF) signals, providing a unique opportunity for assessing resting brain functions with concurrent BOLD (ccBOLD) and CBF signals. Before taking that benefit, it is necessary to validate the utility of ccBOLD signal for resting-state analysis using conventional BOLD (cvBOLD) signal acquired without ASL modulations. To address this technical issue, resting cvBOLD and ASL perfusion MRI were acquired from a large cohort (n = 89) of healthy subjects. Four widely used resting-state brain function analyses were conducted and compared between the two types of BOLD signal, including the posterior cingulate cortex (PCC) seed-based functional connectivity (FC) analysis, independent component analysis (ICA), analysis of amplitude of low frequency fluctuation (ALFF), and analysis of regional homogeneity (ReHo). Consistent default mode network (DMN) as well as other resting-state networks (RSNs) were observed from cvBOLD and ccBOLD using PCC-FC analysis and ICA. ALFF from both modalities were the same for most of brain regions but were different in peripheral regions suffering from the susceptibility gradients induced signal drop. ReHo showed difference in many brain regions, likely reflecting the SNR and resolution differences between the two BOLD modalities. The DMN and auditory networks showed highest CBF values among all RSNs. These results demonstrated the feasibility of ASL perfusion MRI for assessing resting brain functions using its concurrent BOLD in addition to CBF signal, which provides a potentially useful way to maximize the utility of ASL perfusion MRI.

Figure 1. FC results from PCC seed-based analyses showed very similar pattern between conventional BOLD (cvBOLD) (A) and concurrent BOLD (ccBOLD) from ASL data (B).

Only minor differences (C) were observed for conventional BOLD comparing with concurrent BOLD (cvBOLD vs. ccBOLD). Threshold was set as FWE corrected p<0.05.

Figure 2. Resting-state networks (RSNs) identified from ICA analysis of conventional BOLD (up-levels) and concurrent BOLD (lower-levels) data.

RSN1: default mode network (DMN); RSN 2: left attention networks; RSN 3: right attention network; RSN 4: primary visual network; RSN 5: secondary visual network; RSN 6: sensorimotor network; RSN 7: auditory network; RSN 8: executive network; RSN 9: dorsal medial prefrontal network (DMPFC); RSN 10: ventral medial prefrontal network (VMPFC); RSN 11: salience network, RSN 12: medial temporal limbic network.

Figure 3. The Dice's similarity coefficients of the 12 RSNs between two BOLD modalities at the group level.

Figure 4. The averaged Dice's similarity coefficients of the 12 RSNs between two BOLD modalities at the individual level.

Figure 5. Mean CBF values extracted from the 12 resting-state networks by ICA analyses.

Significant difference was observed only in the VMPFC, with concurrent BOLD (ccBOLD) showed lower CBF values than conventional BOLD (cvBOLD). Error bar represented standard error. * p<0.05.

Figure 6. The map of averaged CBF across subjects (A) and the overlays of DMN (B & C) and auditory network acquired from cvBOLD and ccBOLD (D & E).

Figure 7. Mean ALFF values extracted from the 12 resting-state networks by ICA analyses.

Significant difference was observed in the primary visual, auditory, DMPFC, salience and limbic network. Error bar represented standard error. * p<0.05.

Figure 8. Mean ReHo values extracted from the 12 resting-state networks by ICA analyses.

Significant difference was observed in all RSNs except DMN network. Error bar represented standard error. * p<0.05.